Package: afthd 1.1.0

Atanu Bhattacharjee

afthd: Accelerated Failure Time for High Dimensional Data with MCMC

Functions for Posterior estimates of Accelerated Failure Time(AFT) model with MCMC and Maximum likelihood estimates of AFT model without MCMC for univariate and multivariate analysis in high dimensional gene expression data are available in this 'afthd' package. AFT model with Bayesian framework for multivariate in high dimensional data has been proposed by Prabhash et al.(2016) <doi:10.21307/stattrans-2016-046>.

Authors:Atanu Bhattacharjee [aut, cre, ctb], Gajendra Kumar Vishwakarma [aut, ctb], Pragya Kumari [aut, ctb]

afthd_1.1.0.tar.gz
afthd_1.1.0.tar.gz(r-4.5-noble)afthd_1.1.0.tar.gz(r-4.4-noble)
afthd_1.1.0.tgz(r-4.4-emscripten)afthd_1.1.0.tgz(r-4.3-emscripten)
afthd.pdf |afthd.html✨
afthd/json (API)

# Install 'afthd' in R:

install.packages('afthd', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC
c++– GNU Standard C++ Library v3

Datasets:

hdata - Head and neck cancer data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 7 scripts 289 downloads 14 exports 55 dependencies

Last updated 3 years agofrom:5ec629860e. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 14 2024
R-4.5-linux	OK	Oct 14 2024

Exports:aftbybmv lgnbymv lgnbyuni lgstbymv lgstbyuni pvaft rglaft rglwbysm rglwbysu wbyAgmv wbyscrkm wbyscrku wbysmv wbysuni

Dependencies:abind bbmle bdsmatrix BH boot cli coda codetools cpp11 dplyr fansi fastGHQuad foreach generics glmnet glue iterators lattice lifecycle lubridate magrittr MASS Matrix mgcv mvtnorm nlme numDeriv photobiology pillar pkgconfig plyr polynom purrr R2jags R2WinBUGS R6 Rcpp RcppArmadillo RcppEigen rjags rlang rstpm2 shape splus2R stringi stringr survival tibble tidyr tidyselect timechange utf8 vctrs withr zoo

Help page	Topics
Bayesian multivariate analysis of parametric AFT model with minimum deviance (DIC) among weibull, log normal and log logistic distribution.	aftbybmv
Head and neck cancer data	hdata
Bayesian multivariate analysis of AFT model with log normal distribution.	lgnbymv
Bayesian univariate analysis of AFT model with log normal distribution.	lgnbyuni
Multivariate estimates of AFT model with log logistic distribution using MCMC.	lgstbymv
Univariate estimates of AFT model with log logistic distribution using MCMC.	lgstbyuni
Estimates of univariate covariates using Accelerated Failure time (AFT) model without MCMC.	pvaft
Estimates of selected univariate covariates(using regularization) in AFT model without MCMC.	rglaft
Bayesian multivariate analysis of AFT model for selected covariates using regularization method.	rglwbysm
Bayesian univariate analysis of AFT model for selected covariates using regularization method.	rglwbysu
Multivariate estimates of AFT model with weibull distribution using MCMC that supports augmented data.	wbyAgmv
Bayesian multivariate estimates for competing risk gene expression data using AFT model.	wbyscrkm
Bayesian univariate estimates for competing risk gene expression data using AFT model.	wbyscrku
Posterior multivariate estimates of AFT model with weibull distribution using MCMC.	wbysmv
Posterior univariate estimates of AFT model with weibull distribution using MCMC.	wbysuni

Package: afthd 1.1.0

afthd: Accelerated Failure Time for High Dimensional Data with MCMC

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)